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DESCRIPTION: '\n\n DeepPhish: Simulating the Malicious Use of AI\n\n
Ivan Torroledo\n\n Machine Learning and Artificial Intelligence have bec
ome essential to\n any effective cyber security and defense strategy aga
inst unknown\n attacks. In the battle against cybercriminals\, AI-enhanc
ed detection\n systems are markedly more accurate than traditional manua
l\n classification. Through intelligent algorithms\, detection systems h
ave\n been able to identify patterns and detect phishing URLs with 98.7%
\n accuracy\, giving the advantage to defensive teams. However\, if AI i
s\n being used to prevent attacks\, what is stopping cyber criminals fro
m\n using the same technology to defeat both traditional and AI-based\n
cyber-defense systems? This hypothesis is of urgent importance - there\n
is a startling lack of research on the potential consequences of the\n
weaponization of Machine Learning as a threat actor tool. In this\n ta
lk\, we are going to review how threat actors could exponentially\n impr
ove their phishing attacks using AI to bypass\n machine-learning-based p
hishing detection systems. To test this\n hypothesis\, we designed an ex
periment in which\, by identifying how\n threat actors deploy their atta
cks\, we took on the role of an attacker\n in order to test how they may
use AI in their own way. In the end\, we\n developed an AI algorithm\,
called DeepPhish\, that learns effective\n patterns used by threat actor
s and uses them to generate new\, unseen\,\n and effective attacks based
on attacker data. Our results show that\,\n by using DeepPhish\, two un
covered attackers were able to increase\n their phishing attacks effecti
veness from 0.69% to 20.9%\, and 4.91% to\n 36.28%\, respectively.\n\n
Ivan Torroledo is the lead data scientist in the Cyxtera Research\n org
anization. In this role\, he develops and implements Machine and\n Deep
Learning algorithms to enhance phishing detection\, network\n security\,
fraud detection\, and malware mitigation. Ivan is also highly\n interes
ted in research on the application of Machine and Deep Learning\n in hig
h energy physics and astrophysics. Before joining Cyxtera\, he\n worked
at the Central Bank of Colombia\, applying high performance\n computing
tools to monetary policy analysis. He is passionate about\n applying the
most advanced scientific knowledge to cyber security\n industry. Ivan h
olds degrees in Economics and Physics.\n\n '\n\n
DTEND:20180811T184000Z
DTSTART:20180811T182000Z
LOCATION:AIV - Caesars Promenade Level - Florentine BR 3
SUMMARY:DeepPhish: Simulating the Malicious Use of AI
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